Result for 05DB3B16E16409A107FDFF43739768C7F0AB154C

Query result

Key Value
FileName./usr/share/doc/python-pycuda-doc/html/search.html
FileSize3079
MD50C8D515064ED7E2961DE9C83CDA034B9
SHA-105DB3B16E16409A107FDFF43739768C7F0AB154C
SHA-2568BB768527E9D7D4AAEBC9D6080A43BC5A80E2CEF3D18F19191D3442713250FB3
SSDEEP48:GmnpHTffvhx0xpFLLq0kW6Zv+djUrPnF4t5K:RTffT0/FCnW6Za8vOe
TLSHT1C3516315ECE2D40280628AE6E4F2F80E6EC1E45797058C48B0CC86A96FC6FC94E5F69D
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize120940
MD5C11A2D31FECBE0868A8E71B46809B508
PackageDescriptionmodule to access Nvidia‘s CUDA computation API (documentation) PyCUDA lets you access Nvidia‘s CUDA parallel computation API from Python. Several wrappers of the CUDA API already exist–so what’s so special about PyCUDA? * Object cleanup tied to lifetime of objects. This idiom, often called RAII in C++, makes it much easier to write correct, leak- and crash-free code. PyCUDA knows about dependencies, too, so (for example) it won’t detach from a context before all memory allocated in it is also freed. * Convenience. Abstractions like pycuda.driver.SourceModule and pycuda.gpuarray.GPUArray make CUDA programming even more convenient than with Nvidia’s C-based runtime. * Completeness. PyCUDA puts the full power of CUDA’s driver API at your disposal, if you wish. * Automatic Error Checking. All CUDA errors are automatically translated into Python exceptions. * Speed. PyCUDA’s base layer is written in C++, so all the niceties above are virtually free. * Helpful Documentation. . This package contains HTML documentation and example scripts.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython-pycuda-doc
PackageSectioncontrib/doc
PackageVersion2016.1-1
SHA-18BAFFD3C51E55146A1D420A04E2F4DEA57C0863C
SHA-256BFC099C7B4E1437D4D4D83206F67E339EB8BB75C1A645039158F17B8C2772062